[1] ".GlobalEnv"        "package:RSQLite"   "package:tictoc"    "package:car"      
 [5] "package:carData"   "package:forcats"   "package:stringr"   "package:dplyr"    
 [9] "package:purrr"     "package:readr"     "package:tidyr"     "package:tibble"   
[13] "package:ggplot2"   "package:tidyverse" "package:MASS"      "package:knitr"    
[17] "package:stats"     "package:graphics"  "package:grDevices" "package:utils"    
[21] "package:datasets"  "package:methods"   "Autoloads"         "package:base"

1 Visualización de datos.

Todos los ejemplos han sido extraídos del libro R in action de Rober Kabacoff. Capitulo 19

1.1 Ejemplo 1.

library(ggplot2)
p<-ggplot(data=mtcars, aes(x=wt, y=mpg)) +
   geom_point(pch=17, color="blue", size=2) +
   geom_smooth(method="lm", color="red", linetype=2) +
   labs(title="Automobile Data", x="Weight", y="Miles Per Gallon")
show(p)

1.2 Ejemplo 2.

# ?mtcars
mtcars$am <- factor(mtcars$am, levels=c(0,1),
                              labels=c("Automatic", "Manual"))
mtcars$vs <- factor(mtcars$vs, levels=c(0,1),
                        labels=c("V-Engine", "Straight Engine"))
mtcars$cyl <- factor(mtcars$cyl)
#Next, generate a plot using the following code:
library(ggplot2)
ggplot(data=mtcars, aes(x=hp, y=mpg,
       shape=cyl, color=cyl)) +
       geom_point(size=3) +
       facet_grid(am~vs) +
       labs(title="Automobile Data by Engine Type",
            x="Horsepower", y="Miles Per Gallon")

1.3 Ejemplo 3. Geoms

data(singer, package="lattice")
ggplot(singer, aes(x=height)) + geom_histogram()

ggplot(singer, aes(x=voice.part, y=height)) + geom_boxplot()

# Reordenación de un factor, según una función aplicado a una variable
ggplot(singer, aes(x=reorder(voice.part,-height,mean), y=height)) + geom_boxplot()

1.4 Ejemplo 4. Opciones GEOMS

data(Salaries, package="car")
library(ggplot2)
ggplot(Salaries, aes(x=rank, y=salary)) +
       geom_boxplot(fill="cornflowerblue",
       color="black", notch=TRUE)+
       geom_point(position="jitter", color="blue", alpha=.5)+
       geom_rug(side="l", color='black')

1.5 Ejemplo 5.Opciones GEOMS

library(ggplot2)
data(singer, package="lattice")
ggplot(singer, aes(x=voice.part, y=height)) +
       geom_violin(fill="lightblue") +
       geom_boxplot(fill="lightgreen", width=.2)

1.6 Ejemplo 6.Agrupamientos (Grouping)

data(Salaries, package="car")
        library(ggplot2)
        ggplot(data=Salaries, aes(x=salary, fill=rank)) +
               geom_density(alpha=.3)

1.7 Ejemplo 7.Agrupamientos (Grouping)

ggplot(Salaries, aes(x=yrs.since.phd, y=salary, color=rank,
       shape=sex)) + geom_point()

ggplot(Salaries, aes(x=yrs.since.phd, y=salary, color=rank,shape=sex)) + geom_point()+scale_shape_manual(values=c(19,7))+scale_color_manual(values=c('black','red','green'))

1.8 Ejemplo 8.Agrupamientos (Grouping)

ggplot(Salaries, aes(x=rank, fill=sex)) +
       geom_bar(position="stack") + labs(title='position="stack"')

ggplot(Salaries, aes(x=rank, fill=sex)) +
       geom_bar(position="dodge") + labs(title='position="dodge"')+scale_fill_manual(values=c('black','yellow'))+scale_x_discrete(labels=c('Profesor\nAsistente','Profesor\nAsociado','Profesor'))

ggplot(Salaries, aes(x=rank, fill=sex)) +
       geom_bar(position="fill") + labs(title='position="fill"')

1.9 Ejemplo 9.Agrupamientos (Grouping)

ggplot(Salaries, aes(x=rank, fill=sex))+ geom_bar()

        ggplot(Salaries, aes(x=rank)) + geom_bar(fill="red")

        ggplot(Salaries, aes(x=rank, fill="red")) + geom_bar()

1.10 Ejemplo 10. Facets

data(singer, package="lattice")
library(ggplot2)
ggplot(data=singer, aes(x=height, fill=voice.part)) +
       geom_density() +
       facet_grid(voice.part~.)

1.11 Ejemplo 11. Líneas de Ajuste, suavizado, (Smooth)

data(Salaries, package="car")
library(ggplot2)
ggplot(data=Salaries, aes(x=yrs.since.phd, y=salary)) +
       geom_smooth() + geom_point()

1.12 Ejemplo 12.Líneas de Ajuste, suavizado, (Smooth)

ggplot(data=Salaries, aes(x=yrs.since.phd, y=salary,
                          linetype=sex, shape=sex, color=sex)) +
       geom_smooth(method=lm, formula=y~poly(x,2),
                   se=FALSE, size=1) +
       geom_point(size=2)

1.13 Ejemplo 13. Modificando la apariencia de un gráfico. Ejes

data(Salaries,package="car")
library(ggplot2)
ggplot(data=Salaries, aes(x=rank, y=salary, fill=sex)) +
geom_boxplot() +
scale_x_discrete(breaks=c("AsstProf", "AssocProf", "Prof"),
                        labels=c("Assistant\nProfessor",
                                 "Associate\nProfessor",
"Full\nProfessor")) + scale_y_continuous(breaks=c(50000, 100000, 150000, 200000),
                          labels=c("$50K", "$100K", "$150K", "$200K")) +
       labs(title="Faculty Salary by Rank and Sex", x="", y="")

1.14 Ejemplo 14.Modificando la apariencia de un gráfico. Leyendas

data(Salaries,package="car")
library(ggplot2)
ggplot(data=Salaries, aes(x=rank, y=salary, fill=sex)) +
geom_boxplot() +
scale_x_discrete(breaks=c("AsstProf", "AssocProf", "Prof"),
                        labels=c("Assistant\nProfessor",
                                 "Associate\nProfessor",
"Full\nProfessor")) + scale_y_continuous(breaks=c(50000, 100000, 150000, 200000),
                     labels=c("$50K", "$100K", "$150K", "$200K")) +
       labs(title="Faculty Salary by Rank and Gender",
            x="", y="", fill="Gender") +
       theme(legend.position=c(.1,.8))

1.15 Ejemplo 15.Modificando la apariencia de un gráfico. Escalas para variables continuas.

ggplot(mtcars, aes(x=wt, y=mpg, size=disp)) +
               geom_point(shape=21, color="black", fill="cornsilk") +
                labs(x="Weight", y="Miles Per Gallon",
                     title="Bubble Chart", size="Engine\nDisplacement")

1.16 Ejemplo 16.Modificando la apariencia de un gráfico. Escalas para variables discretas. Manual

data(Salaries, package="car")
ggplot(data=Salaries, aes(x=yrs.since.phd, y=salary, color=rank)) +
scale_color_manual(values=c("orange", "olivedrab", "navy")) + geom_point(size=2)

1.17 Ejemplo 17.Modificando la apariencia de un gráfico. Escalas para variables discretas. Automática

ggplot(data=Salaries, aes(x=yrs.since.phd, y=salary, color=rank)) +
       scale_color_brewer(palette="Set1") + geom_point(size=2)

1.18 Ejemplo 18.Escalas de colores.

library(RColorBrewer)
display.brewer.all()

1.19 Ejemplo 19.Themes. Personalización de las opciones de un gráfico.

Nota: cambiar package car–>carData ya que los conjuntos de datos se almacenan en una librería distinta

data(Salaries, package="carData")
        library(ggplot2)
        mytheme <- theme(plot.title=element_text(face="bold.italic",
                         size="14", color="brown"),
                         axis.title=element_text(face="bold.italic",
                            size=10, color="brown"),
                         axis.text=element_text(face="bold", size=9,
                            color="darkblue"),
                         panel.background=element_rect(fill="white",
                            color="darkblue"),
                         panel.grid.major.y=element_line(color="grey",
                            linetype=1),
                         panel.grid.minor.y=element_line(color="grey",
                            linetype=2),
                         panel.grid.minor.x=element_blank(),
                         legend.position="top")
        ggplot(Salaries, aes(x=rank, y=salary, fill=sex)) +
               geom_boxplot() +
               labs(title="Salary by Rank and Sex", x="Rank", y="Salary") +
               mytheme

1.20 Ejemplo 20. Multiple graphs per page

 data(Salaries, package="carData")
        library(ggplot2)
        p1 <- ggplot(data=Salaries, aes(x=rank)) + geom_bar()
        p2 <- ggplot(data=Salaries, aes(x=sex)) + geom_bar()
        p3 <- ggplot(data=Salaries, aes(x=yrs.since.phd, y=salary)) + geom_point()
        library(gridExtra)
        grid.arrange(p1, p2, p3, ncol=3)

        grid.arrange(p1, p2, p3, nrow=3)

        grid.arrange(p1, p2, p3, nrow=2, ncol=2)

1.21 Ejemplo 21. Saving graphs

 myplot <- ggplot(data=mtcars, aes(x=mpg)) + geom_histogram()
ggsave(file="mygraph.png", plot=myplot, width=5, height=4)

1.22 Ejemplo 22. Interactive graph

library(plotly)
data(Salaries, package="carData")
        library(ggplot2)
        mytheme <- theme(plot.title=element_text(face="bold.italic",
                         size="14", color="brown"),
                         axis.title=element_text(face="bold.italic",
                            size=10, color="brown"),
                         axis.text=element_text(face="bold", size=9,
                            color="darkblue"),
                         panel.background=element_rect(fill="white",
                            color="darkblue"),
                         panel.grid.major.y=element_line(color="grey",
                            linetype=1),
                         panel.grid.minor.y=element_line(color="grey",
                            linetype=2),
                         panel.grid.minor.x=element_blank(),
                         legend.position="top")
        p<-ggplot(Salaries, aes(x=rank, y=salary, fill=sex)) +
               geom_boxplot() +
               labs(title="Salary by Rank and Sex", x="Rank", y="Salary") +
               mytheme
        
        ggplotly(p)
        q<-ggplot(mtcars, aes(x=wt, y=mpg, size=disp)) +
               geom_point(shape=21, color="black", fill="cornsilk") +
                labs(x="Weight", y="Miles Per Gallon",
                     title="Bubble Chart", size="Engine\nDisplacement")
        ggplotly(q)